A tiny remote-controlled aircraft modelled on an insect will become Britain's latest weapon against terror. The Dragonfly drone – which can fit in the palm of a hand - will spy on enemy positions and gather intelligence for the military and British agents. It is inspired by the biology of a dragonfly, with four flapping wings and four legs to enable it to fly through the air seamlessly and perch on a windowsill to spy on terrorists. The gadget could even fly into heavily guarded rooms full of jihadists and provide soldiers on the battlefield a picture of what is going on. It is one of the futuristic pieces of kit currently being developed for the Ministry of Defence and the UK's security forces as part of the MoD's new innovation project.

Tesla is working on the next generation of its Autopilot system, which could ultimately lead to a driverless car. Reports this week claim new hardware will significantly boost the cars' existing Autopilot features. They include assisted steering and parking with improvements to radar sensors and cameras to detect hazards. Cars with the next generation hardware would also receive regular software updates, which could lead to level 4 autonomous driving – one step away from fully autonomous vehicles. New hardware will significantly boost Tesla's Autopilot features, including assisted steering and parking, with improvements to radar sensors and cameras to detect hazards. The next improvement in Autopilot 2.0 are set to push the cars closer to fully autonomous vehicles Reports indicate that the next generation of Tesla's Autopilot will include a forward facing triple camera to'see' the road ahead.

Barclays, the UK bank, is to replace the password system on its phone banking service with personal voice recognition. 'Unlike a password, each person's voice is as unique as a fingerprint,' said Steven Cooper, Barclays' head of personal banking. Yet the reality is we have no idea whether either fingerprints or voices are unique at all. 'Unlike a password, each person's voice is as unique as a fingerprint,' said Steven Cooper, Barclays' head of personal banking. Yet the reality is we have no idea whether either fingerprints or voices are unique at all.

If only walking through the airport always looked this dreamy. When everyone wants their 30 seconds of Internet fame, what happens to our IRL relationships? A whole lot of drama and angst, as imagined by Dmitry Nikiforov and Aleksei Korneev, the makers of Delete My Photos, a Russian film following a young man's dreams of developing a new dating app. As many parts of our lives are these days, their trailer is bathed in filters -- a unique approach to a tool that's as become second-nature as selfies. They ran key scenes through mobile photo editor Prisma, which uses convolutional neural networks to combine photos with artistic styles, modeled on, for instance, Van Gogh and Roy Lichtenstein.

On Wednesday, Tesla said one of its customers in Beijing was caught unprepared last week when his car, which had autopilot enabled, sideswiped another vehicle that was partially parked off the side of the road. The accident caused some damage, according to Tesla, but nobody was hurt. Tesla's analysis of the vehicle data logs showed that the driver didn't have his hands on the wheel. The driver doesn't appear to dispute that account, accusing Tesla salespeople of misleading him into thinking that the car had fully self-driving capabilities. Here's how Tesla described the crash in a statement to The Washington Post: The customer's dash cam video shows that the Tesla was being driven on a highway in China where a vehicle was parked on the left shoulder straddling the left lane. The Tesla was following closely behind the car in front of it when the lead car moved to the right to avoid hitting the parked car.

For many years I lived in Eugene, Oregon, also known as "track-town USA" for its long tradition in track and field. Each summer high-profile meets like the United States National Championships or Olympic Trials would bring world-class competitors to the University of Oregon's Hayward Field. It was exciting to bump into great athletes at the local cafe or ice cream shop, or even find myself lifting weights or running on a track next to them. One morning I was shocked to be passed as if standing still by a woman running 400-meter repeats. Her training pace was as fast as I could run a flat out sprint over a much shorter distance.

Alex Honnold has his own verb. "To honnold"--usually written as "honnolding"--is to stand in some high, precarious place with your back to the wall, looking straight into the abyss. The verb was inspired by photographs of Honnold in precisely that position on Thank God Ledge, located 1,800 feet off the deck in Yosemite National Park. Honnold side-shuffled across this narrow sill of stone, heels to the wall, toes touching the void, when, in 2008, he became the first rock climber ever to scale the sheer granite face of Half Dome alone and without a rope. Had he lost his balance, he would have fallen for 10 long seconds to his death on the ground far below. Honnold is history's greatest ever climber in the free solo style, meaning he ascends without a rope or protective equipment of any kind. Above about 50 feet, any fall would likely be lethal, which means that, on epic days of soloing, he might spend 12 or more hours in the Death Zone. On the hardest parts of some climbing routes, his fingers will have no more contact with the rock than most people have with the touchscreens of their phones, while his toes press down on edges as thin as sticks of gum. Just watching a video of Honnold climbing will trigger some degree of vertigo, heart palpitations, or nausea in most people, and that's if they can watch them at all. Even Honnold has said that his palms sweat when he watches himself on film. All of this has made Honnold the most famous climber in the world.

The invention of religion is a big bang in human history. Gods and spirits helped explain the unexplainable, and religious belief gave meaning and purpose to people struggling to survive. But what if everything we thought we knew about religion was wrong? What if belief in the supernatural is window dressing on what really matters--elaborate rituals that foster group cohesion, creating personal bonds that people are willing to die for. Anthropologist Harvey Whitehouse thinks too much talk about religion is based on loose conjecture and simplistic explanations. Whitehouse directs the Institute of Cognitive and Evolutionary Anthropology at Oxford University. For years he's been collaborating with scholars around the world to build a massive body of data that grounds the study of religion in science. Whitehouse draws on an array of disciplines--archeology, ethnography, history, evolutionary psychology, cognitive science--to construct a profile of religious practices. Whitehouse's fascination with religion goes back to his own groundbreaking field study of traditional beliefs in Papua New Guinea in the 1980s.

Following the seminal idea of Tukey, data depth is a function that measures how close an arbitrary point of the space is located to an implicitly defined center of a data cloud. Having undergone theoretical and computational developments, it is now employed in numerous applications with classification being the most popular one. The R-package ddalpha is a software directed to fuse experience of the applicant with recent achievements in the area of data depth and depth-based classification. ddalpha provides an implementation for exact and approximate computation of most reasonable and widely applied notions of data depth. These can be further used in the depth-based multivariate and functional classifiers implemented in the package, where the $DD\alpha$-procedure is in the main focus. The package is expandable with user-defined custom depth methods and separators. The implemented functions for depth visualization and the built-in benchmark procedures may also serve to provide insights into the geometry of the data and the quality of pattern recognition.

We consider the problem of estimating the mean and covariance of a distribution from iid samples in $\mathbb{R}^n$, in the presence of an $\eta$ fraction of malicious noise; this is in contrast to much recent work where the noise itself is assumed to be from a distribution of known type. The agnostic problem includes many interesting special cases, e.g., learning the parameters of a single Gaussian (or finding the best-fit Gaussian) when $\eta$ fraction of data is adversarially corrupted, agnostically learning a mixture of Gaussians, agnostic ICA, etc. We present polynomial-time algorithms to estimate the mean and covariance with error guarantees in terms of information-theoretic lower bounds. As a corollary, we also obtain an agnostic algorithm for Singular Value Decomposition.